Environ Monit Assess. 2025 Dec 11;198(1):40. doi: 10.1007/s10661-025-14870-1.
ABSTRACT
Low-cost particulate matter (PM) sensors are increasingly used for personal and environmental air quality monitoring due to their affordability and accessibility. Recent advancements make these sensors suitable for occupational settings, but their accuracy in such settings remains uncertain. This study calibrated the AirBeam 2 and AirBeam 3 against the Thermo Scientific Personal DataRAM PDR-1500 to assess their efficacy at measuring high PM concentrations, such as those in occupational exposure settings, using engine exhaust and biomass smoke as PM sources. Laboratory calibrations were conducted using a sealed chamber. Linear and polynomial regressions assessed agreement with the PDR-1500, while breakpoint analyses identified thresholds where sensor performance shifted. Field calibrations using the AirBeam 2s evaluated real-world performance and user preferences. The AirBeam 2 exhibited a novel issue where PM₁ readings exceeded PM₂.₅ at concentrations > 50 µg/m3, which was corrected through reprogramming. Polynomial models outperformed linear ones for both devices and the AirBeam 3 performed better with engine exhaust than biomass smoke (linear calibration coefficients 0.192 vs 0.102, respectively), while the AirBeam 2 performed better with biomass smoke than engine exhaust (coefficients 0.323 vs 0.274, respectively). Breakpoints suggested the AirBeam 2s may be better for high concentrations, while the AirBeam 3s were more sensitive at lower concentrations. In the field, the AirBeam 2s recorded lower mean PM concentrations than the PDR-1500 and were more influenced by environmental conditions, yet participants (n = 9) who were recruited to perform field calibrations with both devices preferred the AirBeam. While sensor performance can vary by PM source, concentration, and environmental factors, these findings suggest AirBeams can be a useful option for preliminary occupational exposure assessments after careful calibration and validation prior to use.
PMID:41379328 | DOI:10.1007/s10661-025-14870-1